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Do Agents Dream of Electric Sheep?: Improving Generalization in
  Reinforcement Learning through Generative Learning

Do Agents Dream of Electric Sheep?: Improving Generalization in Reinforcement Learning through Generative Learning

12 March 2024
Giorgio Franceschelli
Mirco Musolesi
    AI4CE
ArXivPDFHTML

Papers citing "Do Agents Dream of Electric Sheep?: Improving Generalization in Reinforcement Learning through Generative Learning"

5 / 5 papers shown
Title
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
303
11,909
0
04 Mar 2022
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit
  Partial Observability
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Dibya Ghosh
Jad Rahme
Aviral Kumar
Amy Zhang
Ryan P. Adams
Sergey Levine
OffRL
270
109
0
13 Jul 2021
Bridging Imagination and Reality for Model-Based Deep Reinforcement
  Learning
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning
Guangxiang Zhu
Minghao Zhang
Honglak Lee
Chongjie Zhang
OffRL
71
17
0
23 Oct 2020
Improving Generalization in Reinforcement Learning with Mixture
  Regularization
Improving Generalization in Reinforcement Learning with Mixture Regularization
Kaixin Wang
Bingyi Kang
Jie Shao
Jiashi Feng
104
116
0
21 Oct 2020
Decoupling Representation Learning from Reinforcement Learning
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke
Kimin Lee
Pieter Abbeel
Michael Laskin
SSL
DRL
280
339
0
14 Sep 2020
1